class_docstr: Character-level CNN encoder to generate word representations, as input to
  RNN encoder.
docstr: Maximum input length supported by the encoder.
docstr_tok: ["Maximum","input","length","supported","by","the","encoder","."]
code: def max_positions(self):
      """Maximum input length supported by the encoder."""
      return int(1e5)
  
imports: import logging
  from ast import literal_eval
  import torch
  import torch.nn.functional
  from fairseq.models import FairseqEncoder, register_model, register_model_architecture
  from pytorch_translate import char_encoder, model_constants, rnn, utils, vocab_constants
  from pytorch_translate.common_layers import Embedding, VariableTracker
  from pytorch_translate.data.dictionary import TAGS
label_desc: Use image node_id 6 for calling the CharCNNEncoder obj's underlying member method code with example usage: obj.max_positions() and returns: int